CLIMATIC DETERMINANTS OF IRRIGATED RICE PERFORMANCE IN THE SAHEL .3. CHARACTERIZING ENVIRONMENTS BY SIMULATING CROP PHENOLOGY

Authors
Citation
M. Dingkuhn, CLIMATIC DETERMINANTS OF IRRIGATED RICE PERFORMANCE IN THE SAHEL .3. CHARACTERIZING ENVIRONMENTS BY SIMULATING CROP PHENOLOGY, Agricultural systems, 48(4), 1995, pp. 435-456
Citations number
41
Categorie Soggetti
Agriculture
Journal title
ISSN journal
0308521X
Volume
48
Issue
4
Year of publication
1995
Pages
435 - 456
Database
ISI
SICI code
0308-521X(1995)48:4<435:CDOIRP>2.0.ZU;2-O
Abstract
Agricultural development programs in most countries of the Sahel seek to increase the intensity of irrigated rice production. Variable crop duration and temperature stresses, however, limit yields and calendria l options. In an effort to characterize climatic constraints to rice d ouble-cropping in the region, a field-based model simulating flowering was combined with models predicting maturity and chilling- and heat-i nduced spikelet sterility. Simulations were performed for key sowing d ates, 38 sites and three genotypes based on 10-33 years of weather rec ords. Sowing between mid-September and mid-November was associated wit h near-total spikelet sterility due to chilling in all Sahelian enviro nments. Crop duration was longest in November, increasing by 5 days pe r degree latitude in the continental Sahel. Greatest annual variation in duration was observed in the coastal west and extreme north of the Sahel. Climatic gradients along the courses of the Senegal and Niger r ivers were associated with different annual patterns of duration and s terility. Based on the genotypes available to farmers, local rice-rice cropping calendars left little room for alternative calendars. Achiev ing a greater flexibility for cropping calendars would require the int roduction of alternative short-duration varieties. The model permits t he zonation of the Sahel in terms of calendrial options and varietal r equirements. For a greater spatial resolution of such studies in the f uture, however, the pooling and digitalization of more weather data is recommended.